Bibliographic record
Abstract
After three field flashover failures of EHV hot sticks, two in Canada at 500 kV and one in the USA at 345 kV, a study of the present day maintenance and testing methods was needed. Experimentation does show that rubbing of the fiberglass reinforced plastic (FRF) over aluminum, aged conductors, and galvanizing will deposit micron size conductive particles onto the insulating medium. The need for a new method of testing was suggested because these field failures implied that the testing methods being used might not have been sufficient in sensitivity to find the problems before they caused a field failure. The low voltage testing methods used for hot stick testing will be compared to aerial lift testing per ANSI-A92.2. In so doing, it may become evident that the evolution of hot stick testing needs a quantum leap in sensitivity to prevent future field failures. The reality of moisture having the capability to penetrate through FRF material will be demonstrated several ways. Moisture spots or an accumulation of metallic contamination that cannot be removed by normal cleaning techniques may determine the end of life of EHV hot sticks. Photographs of the conductive contamination will be provided in the technical paper. The metallic material has been found to be difficult to remove in the cleaning process since it is difficult to see with a 100 X microscope. To insure the flashover resistance of this very important insulation, it is recommended to go at least 700 kV for at least five seconds to make sure the flashover resistance is there. In addition work methods will be addressed, stressing the importance of proper care when installing, using, storing, and maintaining these tools to prevent surface contamination that can lead to reduction of the insulating integrity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".